Real-Time Emotion Recognition for Improving the Teaching-Learning Process: A Scoping Review.

IF 2.7 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY Journal of Imaging Pub Date : 2024-12-09 DOI:10.3390/jimaging10120313
Cèlia Llurba, Ramon Palau
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Abstract

Emotion recognition (ER) is gaining popularity in various fields, including education. The benefits of ER in the classroom for educational purposes, such as improving students' academic performance, are gradually becoming known. Thus, real-time ER is proving to be a valuable tool for teachers as well as for students. However, its feasibility in educational settings requires further exploration. This review offers learning experiences based on real-time ER with students to explore their potential in learning and in improving their academic achievement. The purpose is to present evidence of good implementation and suggestions for their successful application. The content analysis finds that most of the practices lead to significant improvements in terms of educational purposes. Nevertheless, the analysis identifies problems that might block the implementation of these practices in the classroom and in education; among the obstacles identified are the absence of privacy of the students and the support needs of the students. We conclude that artificial intelligence (AI) and ER are potential tools to approach the needs in ordinary classrooms, although reliable automatic recognition is still a challenge for researchers to achieve the best ER feature in real time, given the high input data variability.

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实时情绪识别改善教-学过程:范围检讨。
情绪识别(ER)在包括教育在内的各个领域越来越受欢迎。人们逐渐认识到,以教育为目的,在课堂上使用ER的好处,比如提高学生的学习成绩。因此,实时急诊被证明是教师和学生的一个有价值的工具。然而,它在教育环境中的可行性需要进一步探索。本综述提供了基于实时ER的学生学习经验,以探索他们的学习潜力和提高他们的学业成绩。目的是提供良好实施的证据和对其成功应用的建议。内容分析发现,就教育目的而言,大多数实践都带来了显著的改进。然而,分析指出了可能阻碍在课堂和教育中实施这些做法的问题;这些障碍包括缺乏学生的隐私和学生的支持需求。我们得出结论,人工智能(AI)和ER是满足普通教室需求的潜在工具,尽管考虑到高输入数据可变性,可靠的自动识别仍然是研究人员实时实现最佳ER特征的挑战。
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来源期刊
Journal of Imaging
Journal of Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.90
自引率
6.20%
发文量
303
审稿时长
7 weeks
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